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PSYB01H3 (260)
Anna Nagy (133)
Lecture

B01 CH12.pdf

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Department
Psychology
Course
PSYB01H3
Professor
Anna Nagy
Semester
Fall

Description
Chapter 12Understanding research results description and correlationStats are used for describing data and making inferences on sample data Scales of Measurement areviewLevels of a variable can be decribed by 4 scales o Nominal no numerical quantitative properties o Ordinal rank order o Interval quantitative properties no absolute 0o Ratio quantitative properties has an absolute 0 Analyzing the results if research investigationDepending on the way the variables are studied there are 3 basic ways of describing the results o Comparing group percentages o Correlating scores of individuals on two variables o Comparing group means Comparing group percentagesExample studying if which females or males like traveling more o Lets say out of 50 females and 50 males 80 of females like to travel60 of males like to travel o Need to focus onbecause of variable of liking travel or disliking travel is nominal Correlating individual scoresUsed when you do not have distinct subject groupsIndividuals are measured on 2 variables o Each variable has a range of numerical valuesExample do people who sit near the front receive higher grades Comparing group meansExample studying effect of exposure to an aggressive adult on childrens play o On average how many aggressive acts did the children perform during play in both groupsAggression is a ratio scale variable because there is a true zero and equal intervals Frequency distributionsWhen analyzing results it is useful to start by making a frequency distribution of the dataFrequency Distribution indicates the number of individuals that receive each possible score on a variable o Useful to look at this in terms of sExample how many students in a class received a specific score on an exam Graphing frequency Distributions
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